Harman, M;
Jia, Y;
Mateo, PR;
Polo, M;
(2014)
Angels and monsters: An empirical investigation of potential test effectiveness and efficiency improvement from strongly subsuming higher order mutation.
In: Crnkovic, I and Chechik, M and Grünbacher, P, (eds.)
ASE '14: Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering.
(pp. pp. 397-408).
ACM: New York, USA.
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Abstract
We study the simultaneous test effectiveness and efficiency improvement achievable by Strongly Subsuming Higher Order Mutants (SSHOMs), constructed from 15,792 first order mutants in four Java programs. Using SSHOMs in place of the first order mutants they subsume yielded a 35%-45% reduction in the number of mutants required, while simultaneously improving test efficiency by 15% and effectiveness by between 5.6% and 12%. Trivial first order faults often combine to form exceptionally non-trivial higher order faults; apparently innocuous angels can combine to breed monsters. Nevertheless, these same monsters can be recruited to improve automated test effectiveness and efficiency.
| Type: | Proceedings paper |
|---|---|
| Title: | Angels and monsters: An empirical investigation of potential test effectiveness and efficiency improvement from strongly subsuming higher order mutation |
| Event: | ASE '14: 29th IEEE/ACM International Conference on Automated Software Engineering, 15-19 September 2014, Vasteras, Sweden |
| ISBN-13: | 9781450330138 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/2642937.2643008 |
| Publisher version: | http://dx.doi.org/10.1145/2642937.2643008 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1456659 |
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